Model Base (v.0.3.2)

We constantly work to expand our list of modules. Here is the list of feature extractors, ML models, objectives and optimizers implemented with the latest Modulos AutoML release.

Feature Extractors

  • Autoencoder
  • Cropping
  • Identity
  • Image Identity and Integer Encoding
  • Principal Component Analysis
  • Random Feature Selection
  • Random Pixel Selection
  • T-test Feature Selection
  • Table Preparation with One Hot Encoding
  • Table Preparation with Integer Encoding

Models

  • Convolutional Neural Network (Keras)
  • Convolutional Neural Network incl. Metadata
  • Convolutional Neural Network (Pytorch)
  • LightGBM
  • Neural Architecture Search – Network Morphism
  • Neural Network
  • Random Forest
  • Ridge Regression
  • XGBoost

Objectives

  • Accuracy
  • F1-score (macro)
  • F1-score (micro)
  • Mean Absolute Error (MAE)
  • Median Absolute Error/Deviation (MAD)
  • Precision (micro)
  • R2
  • Recall (micro)
  • Root Mean Squared Error

Optimizers

  • Bayesian
  • Random Search